Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-based Weighted Co-word Analysis.
ABSTRACT: The purpose of this paper is to analyze the characteristics and human effects of atmospheric pollution in the Yangtze River Basin (YRB). An AQI(Air Quality Index)-based weighted co-word method is applied to explore the characteristics of keywords taken from the data, using authoritative media sources and government reports. Hierarchical clustering techniques are utilized to classify and visualize the keywords and display the different types of incidents. The results reveal the following four main clusters: enterprise pollution, coal-burning pollution, traffic pollution, and air pollutants. Cluster 1 is divided into 7 sub-clusters to offer powerful insight into the structural characteristics of industrial activities. This study is one of the first attempts to use a bibliometric approach to visualize the underlying and interconnected sub-clusters from grey data. It also provides an atmospheric pollution mapping for formulating government policies by understanding the human effects of air pollution incidents.
Project description:The Beijing-Tianjin-Hebei (BTH) air pollution transmission channel and its surrounding areas are of importance to air pollution control in China. Based on daily data of air quality index (AQI) and air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) from 2015 to 2016, this study analyzed the spatial and temporal characteristics of air pollution and influencing factors in Henan Province, a key region of the BTH air pollution transmission channel. The result showed that non-attainment days and NAQI were slightly improved at the provincial scale during the study period, whereas that in Hebi, Puyang, and Anyang became worse. PM2.5 was the largest contributor to the air pollution in all cities based on the number of non-attainment days, but its mean frequency decreased by 21.62%, with the mean occurrence of O3 doubled. The spatial distribution of NAQI presented a spatial agglomeration pattern, with high-high agglomeration area varying from Jiaozuo, Xinxiang, and Zhengzhou to Anyang and Hebi. In addition, the NAQI was negatively correlated with sunshine duration, temperature, relative humidity, wind speed, and positively to atmospheric pressure and relative humidity in all four clusters, whereas relationships between socioeconomic factors and NAQI differed among them. These findings highlight the need to establish and adjust regional joint prevention and control of air pollution as well as suggest that it is crucially important for implementing effective strategies for O3 pollution control.
Project description:In recent years, many researchers have investigated the association between air pollution and children. However, there has been little research to provide a macroscopic overview in this field. The aim of this study is to characterize the scientific production around the world in this area and map the trends. The relevant literature was searched from 1999 to 2018. To guarantee the quality of the literature, we combined the PubMed and WoS databases. The built-in statistics tools of the Web of Science website were used to display the trend of articles published by year and the distribution of journals. By CiteSpace (5.5.R2), the reference co-citation and burst keywords were extracted. In total, 15,999 target English documents were obtained. We summarized the characteristics of published documents, of research institutes' cooperation, and of the contents. As part of a research hotspot, ten clusters are presented, four popular topics are elaborated. Twenty-four burst words were obtained and analyzed. China has received more attention in recent years. Researchers in this field could carry out more cohorts' studies and fine particulate matter is one good air pollution index. Household air pollution exposure and children's lung function should be paid more attention.
Project description:Although the physical effects of air pollution on humans are well documented, there may be even greater impacts on the emotional state and health. Surveys have traditionally been used to explore the impact of air pollution on people's subjective well-being (SWB). However, the survey techniques usually take long periods to properly match the air pollution characteristics from monitoring stations to each respondent's SWB at both disaggregated spatial and temporal levels. Here, we used air pollution data to simulate fixed-scene images and psychophysical process to examine the impact from only air pollution on SWB. Findings suggest that under the atmospheric conditions in Beijing, negative emotions occur when PM2.5 (particulate matter with a diameter less than 2.5 µm) increases to approximately 150 AQI (air quality index). The British observers have a stronger negative response under severe air pollution compared with Chinese observers. People from different social groups appear to have different sensitivities to SWB when air quality index exceeds approximately 200 AQI.
Project description:Traffic flow forecasting is one of the most important use cases related to smart cities. In addition to assisting traffic management authorities, traffic forecasting can help drivers to choose the best path to their destinations. Accurate traffic forecasting is a basic requirement for traffic management. We propose a traffic forecasting approach that utilizes air pollution and atmospheric parameters. Air pollution levels are often associated with traffic intensity, and much work is already available in which air pollution has been predicted using road traffic. However, to the best of our knowledge, an attempt to improve forecasting road traffic using air pollution and atmospheric parameters is not yet available in the literature. In our preliminary experiments, we found out the relation between traffic intensity, air pollution, and atmospheric parameters. Therefore, we believe that addition of air pollutants and atmospheric parameters can improve the traffic forecasting. Our method uses air pollution gases, including C O , N O , N O 2 , N O x , and O 3 . We chose these gases because they are associated with road traffic. Some atmospheric parameters, including pressure, temperature, wind direction, and wind speed have also been considered, as these parameters can play an important role in the dispersion of the above-mentioned gases. Data related to traffic flow, air pollution, and the atmosphere were collected from the open data portal of Madrid, Spain. The long short-term memory (LSTM) recurrent neural network (RNN) was used in this paper to perform traffic forecasting.
Project description:Conventional regulatory air quality monitoring sites tend to be sparsely located. The availability of lower-cost air pollution sensors, however, allows for their use in spatially dense community monitoring networks, which can be operated by various stakeholders, including concerned residents, organizations, academics, or government agencies. Networks of many community monitors have the potential to fill the spatial gaps between existing government-operated monitoring sites. One potential benefit of finer scale monitoring might be the ability to discern elevated air pollution episodes in locations that have not been identified by government-operated monitoring sites, which might improve public health warnings for populations sensitive to high levels of air pollution. In the Imperial Air study, a large network of low-cost particle monitors was deployed in the Imperial Valley in Southeastern California. Data from the new monitors is validated against regulatory air monitoring. Neighborhood-level air pollution episodes, which are defined as periods in which the PM2.5 (airborne particles with sizes less than 2.5 μm in diameter) hourly average concentration is equal to or greater than 35 μg m-3, are identified and corroborate with other sites in the network and against the small number of government monitors in the region. During the period from October 2016 to February 2017, a total of 116 episodes were identified among six government monitors in the study region; however, more than 10 times as many episodes are identified among the 38 community air monitors. Of the 1426 episodes identified by the community sensors, 723 (51%) were not observed by the government monitors. These findings suggest that the dense network of community air monitors could be useful for addressing current limitations in the spatial coverage of government air monitoring to provide real-time warnings of high pollution episodes to vulnerable populations.
Project description:To effectively control air pollution, it is necessary to obtain a preliminary assessment of air quality. The purpose of this study was to introduce a cloud model method in air pollution assessment. First, the standard cloud models of air pollution indicators were obtained, and the calculating process of numerical characteristics employed by the standard cloud model was explained. Second, the levels of air pollution indicators were presented based on the qualitative and quantitative analysis of cloud models, which realized the uncertainty conversion between qualitative concepts and their corresponding quantitative values, as well as taking the fuzziness and randomness into account. Air quality assessment results including SO2, NO2, CO, O3, PM10 and PM2.5 were analysed. Third, the cloud model adopted in the assessment process of air quality was validated by grey relational analysis, and the results confirmed the validity of cloud model assessment. Fourth, the air pollution level of the air quality index (AQI) was determined, and the fuzziness and randomness of the assessment results were thoroughly analysed by taking entropy and hyper entropy into consideration. Fifth, seasonal variations in different air pollution indicators were analysed to proffer a series of recommendations for government policy decision-makers and travellers. The cloud model provided a new method for air quality assessment.
Project description:Air pollution is associated with a diversity of health effects, and evidence for a causal relationship with specific diseases exists. Exposure to air pollution is ubiquitous and typically beyond the control of the individual; the resulting health burden for the population can be high. Disproportionate effects are seen in individuals who have increased susceptibility to air pollution owing to individual- or community-level characteristics. As studies grow increasingly sophisticated, the understanding of who comprises the susceptible population continuously expands. Characteristics of susceptibility include genetic predisposition; socioeconomic factors; life stage; the presence of preexisting diseases, such as asthma, chronic obstructive pulmonary disease, cystic fibrosis; and the unique population of lung transplant recipients. This review explores how select populations, namely individuals with preexisting pulmonary disease and those living in communities of low socioeconomic status, have an increased susceptibility to the health effects of ambient air pollution. Genetic susceptibility, though a fundamental determinant of risk, is beyond the scope of this review and is not discussed. Strategies designed to mitigate air pollution-related health effects are discussed using a framework that addresses pollution exposure at multiple levels-government, state, community, and the individual. Emission reduction strategies remain the basis for public health protection; however, ancillary harm reduction measures are explored that can be adopted by susceptible communities and individuals.
Project description:Background: Background sites are mainly affected by long-range-transported air pollutants, resulting in potential adverse effects on local atmospheric environments. A 4-5 year observational study was conducted to illustrate the air pollution profile at the Kanazawa University Wajima air monitoring station (KUWAMS), an ideal remote background site in Japan. Methods: Nine polycyclic aromatic hydrocarbons (PAHs) in the particulate phase and various air pollutants were continuously monitored for 4-5 years. Diagnostic ratios of PAHs and back-trajectory analysis were applied to trace the possible sources of the air pollutants collected at the sampling site. Results: The atmospheric concentration of PAHs in the atmosphere at the site decreased from 2014 to 2019, benefit from the predominant air pollution control policy in China and Japan. Common air pollutants including sulfur dioxide (SO2), nitrogen oxides (NOx), ozone, methane (CH4), and non-methane hydrocarbon (NMHC) were detected in low concentrations from 2016 to 2019, while ozone (O3) and particulate matter (PM2.5, PM with a diameter less than 2.5 ?m) were present in high levels that exceeded the Japanese standards. Most air pollutants peaked in spring and showed evident diurnal variations in spring and summer. Conclusions: This is the first study to clarify the atmospheric behaviors of multiple air pollutants at a background site in Japan. Significant external air pollutant impact and unneglectable air pollution were demonstrated at KUWAMS, indicating the importance of studying atmospheric pollution at remote sites.
Project description:Highlights • Variations in air quality in terms of CO, SO2, PM10, O3 and NO2 levels were studied.• The lockdown of Spain was not able to reduce severe air pollution in all its forms.• Significant reductions of NO2 levels were achieved in most cities.• Increases of O3 pollution levels were found in several cities. The COVID-19 pandemic has escalated into one of the largest crises of the 21st Century. The new SARS-CoV-2 coronavirus, responsible for COVID-19, has spread rapidly all around the world. The Spanish Government was forced to declare a nationwide lockdown in view of the rapidly spreading virus and high mortality rate in the nation. This study investigated the impact of short-term lockdown during the period from March 15th to April 12th 2020 on the atmospheric levels of CO, SO2, PM10, O3, and NO2 over 11 representative Spanish cities. The possible influence of several meteorological factors (temperature, precipitation, wind, sunlight hours, minimum and maximum pressure) on the pollutants' levels were also considered. The results obtained show that the 4-week lockdown had significant impact on reducing the atmospheric levels of NO2 in all cities except for the small city of Santander as well as CO, SO2, and PM10 in some cities, but resulted in increase of O3 level. Graphical abstract Image, graphical abstract
Project description:Atmospheric corrosion poses a significant problem with regard to destruction of various materials, especially metals. Observations made over the past decades suggest that the world's climate is changing. Besides global warming, there are also changes in other parameters. For example, average annual precipitation increased by nearly 10% over the course of the 20th century. In Europe, the most significant change, from the atmospheric corrosion point of view, was an increase in SO₂ pollution in the 1970s through the 1980s and a subsequent decrease in this same industrial air pollution and an increase in other types of air pollution, which created a so-called multi-pollutant atmospheric environment. Exposed metals react to such changes immediately, even if corrosion attack started in high corrosive atmospheres. This paper presents a complex evaluation of the effect of air pollution and other environmental parameters and verification of dose/response equations for conditions in the Czech Republic.